• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.880-884
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• 1995

Manufacturing environment is getting characterized by unstable market demand,short product life cycle and timebased competition. For adapting this environment,machine tools have to be further versatile functionally in order to reduce part's set-up time. Unlike existing manufacturing systems mainly to focus on part flow, it is important to control tool flow using fast tool change device and tool delivery device in parallel machines consisting of versatile machine tools, because complete operations on a part can be performed on one machine tool in a single machine set-up. In this paper, under dynamic tool allocation strategy to share tools among machine tools, we propose a real-time tool allocation and operation esequence model with an objective of minimizing flow time using autonomy and negotiation of agents in parallel machines

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.8-14
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• 2007

This paper addresses the allocation planning of the storage location in a warehouse system that the dedicated storage method is used. In the discrete finite time period model, the demands for storage location of products are dynamic for time periods. The planning is to determine the reallocation time period and the storage location of the products in reallocation time period, which minimizes costs. The cost factors are the reallocation cost, the travel cost within warehouse and the surplus storage location cost. A model is formulated, and the property of optimal solution is characterized. The dynamic programming algorithm is developed, and a numerical example is shown.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.510-516
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• 2010

In this paper, a dynamic GTS allocation method of wireless control networks is proposed for the use of factory automation using IEEE 802.15.4 MAC protocol. A superframe of IEEE 802.15.4 is applied to the transmission method of real-time periodic I/O data of wireless control systems within the limited time in factory environment. The method is proposed for efficient transmission of real-time periodic I/O traffic. The simulation results show the average network utilization and available I/O node numbers could be increased by the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1035-1040
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• 2009

We propose a new encoder/decoders based on an tune able wavelength converter(TWC) and an arrayed waveguide grating(AWG) router for large capacity optical CDMA networks. The proposed encoder/decoder treats codewords of wavelength/time 2-D code simultaneously using the dynamic code allocation property of the TWC and the cyclic property of the AWG router, and multiple subscribers can share the encoder/decoder in networks. Feasibility of the structure of the proposed encoder/decoder for dynamic code allocation is tested through simulations using two wavelength/time 2-D codes, which are the generalized multi-wavelength prime code(GMWPC) and the generalized multi-wavelength Reed-Solomon code(GMWRSC). Test results show that the proposed encoder/decoder can increase the channel efficiency not only by increasing the number of simultaneous users without any multiple-access interference but by using a relatively short length CDMA codes.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.141-157
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• 2004

In this paper, we consider broadband satellite systems using MF-TDMA(Multi-Frequency Time Division Multiple Access) scheme. First, we analyze return link, superframe structure, and QoS( Quality of Service) parameters in broadband satellite systems, and mathematically formulate the QoS-based optimal timeslot allocation problem as a nonlinear integer programming problem for broadband satellite systems with clear-sky and rain-fade satellite terminals, and multiple data classes. Next, we modify the proposed problem to solve it within in a fast time, and suggest the QoS-based optimal timeslot allocation scheme. Extensive simulation results show that the proposed scheme finds an optimal solution or a near optimal solution within 5ms at Pentium IV PC.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.482-483
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• 2008

This paper compares particle swarm optimization techniques for PV allocation planning problem in power systems. PV allocation planning problem is formulated as a mixed-integer nonlinear problem. Five variants of PSO techniques are investigated for the applicability on the PV allocation problem. Namely, PSO with constant inertia weight approach (PSO-CIW), PSO with time varying inertia weight (PSO-TVIW), PSO with random inertia weight (PSO-RIW), PSO with constriction factor (PSO-CF) and PSO with time varying acceleration coefficients (PSO-TVAC).

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.862-869
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• 2013

In order to support a cell-independent traffic asymmetry, the conventional TDD system cannot avoid crossed time slot (CTS) interference. Moreover, the TDD/FDD hierarchical overlay cellular systems is taken into account as a generally accepted cell model in a heterogeneous radio environment. In this paper, we propose an interference resolving radio resource allocation technique in a TDD-OFDMA cellular system that overlays a FDD-CDMA cell. In our proposed scheme, we exploit under-used FDD-CDMA uplink resource by TDD mobile abiding by a region based time slot(TS) allocation which in turn mitigates CTS interference considerably. It is demonstrated that combined with under-used resource utilization scheme based on mobile's location, the proposed technique can reduce CTS interference considerably and support the asymmetric traffic in TDD system.

• International Journal of Contents
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• v.7 no.2
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• pp.1-5
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• 2011

Allocation of computing resources is a crucial issue when dealing with a huge number of tasks to be completed according to a given deadline and cost constraints. The task scheduling to several resources (e.g. grid, cloud or a supercomputer) with different characteristics is not trivial, especially if a trade-off in terms of time and cost is considered. We propose an allocation approach able to fulfill the given requirements about time and cost through the use of optimizing techniques and an adaptive behavior. Simulated productions of tasks have been run in order to evaluate the characteristics of the proposed approach.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.117-129
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• 2006

In this paper, we consider broadband satellite networks using MF-TDMA (Multi-Frequency Time Division Multiple Access) scheme. We analyze the number of expected lost packets in each terminal, and mathematically formulate optimal buffer and timeslot allocation model to minimize the weighted sum of the numbers of expected lost packets. We also suggest optimal buffer and timeslot allocation scheme based on Lagrangean relaxation technique to solve the proposed model in a fast time. Extensive experiments show that the proposed scheme provides encouraging results.

• Journal of Information Processing Systems
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• v.20 no.2
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• pp.226-238
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• 2024

Recently, multi-access edge computing (MEC) has emerged as a promising technology to alleviate the computing burden of vehicular terminals and efficiently facilitate vehicular applications. The vehicle can improve the quality of experience of applications by offloading their tasks to MEC servers. However, channel conditions are time-varying due to channel interference among vehicles, and path loss is time-varying due to the mobility of vehicles. The task arrival of vehicles is also stochastic. Therefore, it is difficult to determine an optimal offloading with resource allocation decision in the dynamic MEC system because offloading is affected by wireless data transmission. In this paper, we study computation offloading with resource allocation in the dynamic MEC system. The objective is to minimize power consumption and maximize throughput while meeting the delay constraints of tasks. Therefore, it allocates resources for local execution and transmission power for offloading. We define the problem as a Markov decision process, and propose an offloading method using deep reinforcement learning named deep deterministic policy gradient. Simulation shows that, compared with existing methods, the proposed method outperforms in terms of throughput and satisfaction of delay constraints.